Monitoring biogenic amines,which are metabolic byproducts of shrimp spoilage,is crucial for assessing food quality.Currently,most detection methods for biogenic amines suffer from limitations such as time-consuming pr...Monitoring biogenic amines,which are metabolic byproducts of shrimp spoilage,is crucial for assessing food quality.Currently,most detection methods for biogenic amines suffer from limitations such as time-consuming procedures,complex operations,and delayed results.Colorimetric analysis techniques have gained attention in recent years due to their advantages of short analysis time,simple operation,and suitability for on-site testing.This study successfully developed a series of colorimetric sensor platforms for biogenic amines by loading the natural active ingredient curcumin(CUR)and its derivative of Boron complex BFCUR onto filter paper and electrospun nanofibre films(ENFs),respectively.By analyzing the color response differences of these sensors upon contact with biogenic amines,the colorimetric sensors with superior detection performance were selected and further applied to the visual monitoring and indication of shrimp spoilage processes.展开更多
Flexible fiber sensors,However,traditional methods face challenges in fabricating low-cost,large-scale fiber sensors.In recent years,the thermal drawing process has rapidly advanced,offering a novel approach to flexib...Flexible fiber sensors,However,traditional methods face challenges in fabricating low-cost,large-scale fiber sensors.In recent years,the thermal drawing process has rapidly advanced,offering a novel approach to flexible fiber sensors.Through the preform-tofiber manufacturing technique,a variety of fiber sensors with complex functionalities spanning from the nanoscale to kilometer scale can be automated in a short time.Examples include temperature,acoustic,mechanical,chemical,biological,optoelectronic,and multifunctional sensors,which operate on diverse sensing principles such as resistance,capacitance,piezoelectricity,triboelectricity,photoelectricity,and thermoelectricity.This review outlines the principles of the thermal drawing process and provides a detailed overview of the latest advancements in various thermally drawn fiber sensors.Finally,the future developments of thermally drawn fiber sensors are discussed.展开更多
Developing effective,versatile,and high-precision sensing interfaces remains a crucial challenge in human-machine-environment interaction applications.Despite progress in interaction-oriented sensing skins,limitations...Developing effective,versatile,and high-precision sensing interfaces remains a crucial challenge in human-machine-environment interaction applications.Despite progress in interaction-oriented sensing skins,limitations remain in unit-level reconfiguration,multiaxial force and motion sensing,and robust operation across dynamically changing or irregular surfaces.Herein,we develop a reconfigurable omnidirectional triboelectric whisker sensor array(RO-TWSA)comprising multiple sensing units that integrate a triboelectric whisker structure(TWS)with an untethered hydro-sealing vacuum sucker(UHSVS),enabling reversibly portable deployment and omnidirectional perception across diverse surfaces.Using a simple dual-triangular electrode layout paired with MXene/silicone nanocomposite dielectric layer,the sensor unit achieves precise omnidirectional force and motion sensing with a detection threshold as low as 0.024 N and an angular resolution of 5°,while the UHSVS provides reliable and reversible multi-surface anchoring for the sensor units by involving a newly designed hydrogel combining high mechanical robustness and superior water absorption.Extensive experiments demonstrate the effectiveness of RO-TWSA across various interactive scenarios,including teleoperation,tactile diagnostics,and robotic autonomous exploration.Overall,RO-TWSA presents a versatile and high-resolution tactile interface,offering new avenues for intelligent perception and interaction in complex real-world environments.展开更多
Wearable sensors integrated with deep learning techniques have the potential to revolutionize seamless human-machine interfaces for real-time health monitoring,clinical diagnosis,and robotic applications.Nevertheless,...Wearable sensors integrated with deep learning techniques have the potential to revolutionize seamless human-machine interfaces for real-time health monitoring,clinical diagnosis,and robotic applications.Nevertheless,it remains a critical challenge to simultaneously achieve desirable mechanical and electrical performance along with biocompatibility,adhesion,self-healing,and environmental robustness with excellent sensing metrics.Herein,we report a multifunctional,anti-freezing,selfadhesive,and self-healable organogel pressure sensor composed of cobalt nanoparticle encapsulated nitrogen-doped carbon nanotubes(CoN CNT)embedded in a polyvinyl alcohol-gelatin(PVA/GLE)matrix.Fabricated using a binary solvent system of water and ethylene glycol(EG),the CoN CNT/PVA/GLE organogel exhibits excellent flexibility,biocompatibility,and temperature tolerance with remarkable environmental stability.Electrochemical impedance spectroscopy confirms near-stable performance across a broad humidity range(40%-95%RH).Freeze-tolerant conductivity under sub-zero conditions(-20℃)is attributed to the synergistic role of CoN CNT and EG,preserving mobility and network integrity.The Co N CNT/PVA/GLE organogel sensor exhibits high sensitivity of 5.75 k Pa^(-1)in the detection range from 0 to 20 k Pa,ideal for subtle biomechanical motion detection.A smart human-machine interface for English letter recognition using deep learning achieved 98%accuracy.The organogel sensor utility was extended to detect human gestures like finger bending,wrist motion,and throat vibration during speech.展开更多
As emerging two-dimensional(2D)materials,carbides and nitrides(MXenes)could be solid solutions or organized structures made up of multi-atomic layers.With remarkable and adjustable electrical,optical,mechanical,and el...As emerging two-dimensional(2D)materials,carbides and nitrides(MXenes)could be solid solutions or organized structures made up of multi-atomic layers.With remarkable and adjustable electrical,optical,mechanical,and electrochemical characteristics,MXenes have shown great potential in brain-inspired neuromorphic computing electronics,including neuromorphic gas sensors,pressure sensors and photodetectors.This paper provides a forward-looking review of the research progress regarding MXenes in the neuromorphic sensing domain and discussed the critical challenges that need to be resolved.Key bottlenecks such as insufficient long-term stability under environmental exposure,high costs,scalability limitations in large-scale production,and mechanical mismatch in wearable integration hinder their practical deployment.Furthermore,unresolved issues like interfacial compatibility in heterostructures and energy inefficiency in neu-romorphic signal conversion demand urgent attention.The review offers insights into future research directions enhance the fundamental understanding of MXene properties and promote further integration into neuromorphic computing applications through the convergence with various emerging technologies.展开更多
Fiber-structured ion sensors have gained traction in health monitoring and medical diagnostics owing to their structural flexibility,enhanced sensitivity,and suitability for integration into wearable devices.This stud...Fiber-structured ion sensors have gained traction in health monitoring and medical diagnostics owing to their structural flexibility,enhanced sensitivity,and suitability for integration into wearable devices.This study employed a simple and efficient solutionbased process to fabricate nanofibers containing aggregation-induced emission(AIE)dyes.The resulting AIE nanofibers exhibited stable and intense fluorescence,nanosecond fluorescence lifetime,and low-loss light transport when functioning as active waveguides.Additionally,crossed nanofiber intersections exhibited diffraction-limited emission spots.The AIE nanofibers demonstrate efficient and ionspecific fluorescence quenching in response to Ag^(+).These results support the development of sensing units capable of operating in liquid environments or in direct contact with skin or tissues,facilitating real-time monitoring of ion concentrations for personalized healthcare management.展开更多
The advancement of wearable sensing technologies demands multifunctional materials that integrate high sensitivity,environmental resilience,and intelligent signal processing.In this work,a flexible hydrophobic conduct...The advancement of wearable sensing technologies demands multifunctional materials that integrate high sensitivity,environmental resilience,and intelligent signal processing.In this work,a flexible hydrophobic conductive yarn(FCB@SY)featuring a controllable microcrack structure is developed via a synergistic approach combining ultrasonic swelling and non-solvent induced phase separation(NIPS).By embedding a robust conductive network and engineering microcrack morphology,the resulting sensor achieves an ultrahigh gauge factor(GF≈12,670),an ultrabroad working range(0%-547%),a low detection limit(0.5%),rapid response/recovery time(140 ms/140 ms),and outstanding durability over 10,000 cycles.Furthermore,the hydrophobic surface endowed by conductive coatings imparts exceptional chemical stability against acidic and alkaline environments,as well as reliable waterproof performance.This enables consistent functionality under harsh conditions,including underwater operation.Integrated with machine learning algorithms,the FCB@SY-based intelligent sensing system demonstrates dualmode capabilities in human motion tracking and gesture recognition,offering significant potential for applications in wearable electronics,human-machine interfaces,and soft robotics.展开更多
In the context of the rapid development of artificial intelligence and robotics,their application scenarios are continuously expanding to a variety of complex environments,with increasing attention being paid to the u...In the context of the rapid development of artificial intelligence and robotics,their application scenarios are continuously expanding to a variety of complex environments,with increasing attention being paid to the use of flexible sensors in lowtemperature environments.In this study,an ionic hydrogel was synthesized using acrylamide(AM),hydroxyethyl cellulose(HEC),and lithium chloride(LiCl)as composites.This hydrogel exhibits high adhesion,excellent sensitivity(gauge factor(GF)=2.84),rapid response time(100 ms),exceptional stretch ability(>1776%),high toughness(2.5 MJ/m^(3)),and the ability to maintain detectability at low temperatures(-60℃).HEC imparts reliable mechanical properties to the sensor through hydrogen bonding interactions of its hydroxyl groups.LiCl ensures that the sensor has outstanding antifreezing properties,maintains good conductivity and mechanical performance.Used for robotic attitude detection,the sensor demonstrated accurate recognition of various joint movements at both 20 and -20℃.This technology was extended to industrial operations and maintenance,where a mechanical claw was used to grasp parts at both room temperature and low temperature.A convolutional neural network deep learning algorithm was employed to identify and classify eight types of parts,achieving an impressive recognition accuracy of 98.8%.The polyacrylamide(PAM)/HEC/LiCl hydrogel sensor demonstrates the capability for wide-temperature range detection in flexible robotics,holding significant potential for future applications in human-machine interaction,tactile perception,and related fields.展开更多
Human action recognition(HAR)is crucial for the development of efficient computer vision,where bioinspired neuromorphic perception visual systems have emerged as a vital solution to address transmission bottlenecks ac...Human action recognition(HAR)is crucial for the development of efficient computer vision,where bioinspired neuromorphic perception visual systems have emerged as a vital solution to address transmission bottlenecks across sensor-processor interfaces.However,the absence of interactions among versatile biomimicking functionalities within a single device,which was developed for specific vision tasks,restricts the computational capacity,practicality,and scalability of in-sensor vision computing.Here,we propose a bioinspired vision sensor composed of a Ga N/Al N-based ultrathin quantum-disks-in-nanowires(QD-NWs)array to mimic not only Parvo cells for high-contrast vision and Magno cells for dynamic vision in the human retina but also the synergistic activity between the two cells for in-sensor vision computing.By simply tuning the applied bias voltage on each QD-NW-array-based pixel,we achieve two biosimilar photoresponse characteristics with slow and fast reactions to light stimuli that enhance the in-sensor image quality and HAR efficiency,respectively.Strikingly,the interplay and synergistic interaction of the two photoresponse modes within a single device markedly increased the HAR recognition accuracy from 51.4%to 81.4%owing to the integrated artificial vision system.The demonstration of an intelligent vision sensor offers a promising device platform for the development of highly efficient HAR systems and future smart optoelectronics.展开更多
Diabetes mellitus represents a major global health issue,driving the need for noninvasive alternatives to traditional blood glucose monitoring methods.Recent advancements in wearable technology have introduced skin-in...Diabetes mellitus represents a major global health issue,driving the need for noninvasive alternatives to traditional blood glucose monitoring methods.Recent advancements in wearable technology have introduced skin-interfaced biosensors capable of analyzing sweat and skin biomarkers,providing innovative solutions for diabetes diagnosis and monitoring.This review comprehensively discusses the current developments in noninvasive wearable biosensors,emphasizing simultaneous detection of biochemical biomarkers(such as glucose,cortisol,lactate,branched-chain amino acids,and cytokines)and physiological signals(including heart rate,blood pressure,and sweat rate)for accurate,personalized diabetes management.We explore innovations in multimodal sensor design,materials science,biorecognition elements,and integration techniques,highlighting the importance of advanced data analytics,artificial intelligence-driven predictive algorithms,and closed-loop therapeutic systems.Additionally,the review addresses ongoing challenges in biomarker validation,sensor stability,user compliance,data privacy,and regulatory considerations.A holistic,multimodal approach enabled by these next-generation wearable biosensors holds significant potential for improving patient outcomes and facilitating proactive healthcare interventions in diabetes management.展开更多
The growing prevalence of exercise-induced tibial stress fractures demands wearable sensors capable of monitoring dynamic musculoskeletal loads with medical-grade precision.While flexible pressure-sensing insoles show...The growing prevalence of exercise-induced tibial stress fractures demands wearable sensors capable of monitoring dynamic musculoskeletal loads with medical-grade precision.While flexible pressure-sensing insoles show clinical potential,their development has been hindered by the intrinsic trade-off between high sensitivity and full-range linearity(R^(2)>0.99 up to 1 MPa)in conventional designs.Inspired by the tactile sensing mechanism of human skin,where dermal stratification enables wide-range pressure adaptation and ion-channelregulated signaling maintains linear electrical responses,we developed a dual-mechanism flexible iontronic pressure sensor(FIPS).This innovative design synergistically combines two bioinspired components:interdigitated fabric microstructures enabling pressure-proportional contact area expansion(αP1/3)and iontronic film facilitating self-adaptive ion concentration modulation(αP^(2/3)),which together generate a linear capacitance-pressure response(CαP).The FIPS achieves breakthrough performance:242 kPa^(-1)sensitivity with 0.997linearity across 0-1 MPa,yielding a record linear sensing factor(LSF=242,000).The design is validated across various substrates and ionic materials,demonstrating its versatility.Finally,the FIPS-driven design enables a smart insole demonstrating 1.8%error in tibial load assessment during gait analysis,outperforming nonlinear counterparts(6.5%error)in early fracture-risk prediction.The biomimetic design framework establishes a universal approach for developing high-performance linear sensors,establishing generalized principles for medical-grade wearable devices.展开更多
Aeromagnetic data for center-east Cameroon between the latitudes 3.5° to 4.5°N and longitudes 12° to 12.5°E are used to further study the subsurface area of this part of the geological Province of ...Aeromagnetic data for center-east Cameroon between the latitudes 3.5° to 4.5°N and longitudes 12° to 12.5°E are used to further study the subsurface area of this part of the geological Province of Central Africa and the Congo Craton. The GIS and GEOSOFT v6.5 softwares are used to treat the data. This analysis enabled us to explore our study area from surface right to the base. The Tilt Angle method is used to delineate geological structures and to estimate the depth. The Euler’s deconvolution method is used to estimate the specific depth of structural contacts. We estimate the northern boundary of the Congo Craton and southern boundary of the Pan-African starting from 3°7'N of West to 3°75'N of East. Its depth is estimated around 2.6 km for deep and 0.1 km for shallow while the direction is WSW-ENE and the NW slope varies from 30° to 60°. We obtain that main and minor lineaments exist throughout, from the surface to the base of the area with their principal direction being SW-NE. We also obtain the vertical gradient contact and the quasihorizontal contact. This is proof of the subduction of the Pan-African belt under the Congo Craton due to the intense collision which caused the rejuvenation of the crust. The main consequence of this collision is the formation of pudding and fold structures, beginning from the superficial part right to the base and which caused the intrusion of schistose, chlorite-schist, quartzite in the micaschist and the intrusions of gneiss and garnetiferous schist in the migmatite. In our study, we highlight the presence of 37 major and 523 minor lineaments that localize the circulation of minerals. The probable slope of the lineaments in the northern part of the region varies from 30° to 60° in a SE direction while in the southern part, and it varies from 30° to 60° in a NW direction.展开更多
Gas sensor is an indispensable part of modern society withwide applications in environmental monitoring,healthcare,food industry,public safety,etc.With the development of sensor technology,wireless communication,smart...Gas sensor is an indispensable part of modern society withwide applications in environmental monitoring,healthcare,food industry,public safety,etc.With the development of sensor technology,wireless communication,smart monitoring terminal,cloud storage/computing technology,and artificial intelligence,smart gas sensors represent the future of gassensing due to their merits of real-time multifunctional monitoring,earlywarning function,and intelligent and automated feature.Various electronicand optoelectronic gas sensors have been developed for high-performancesmart gas analysis.With the development of smart terminals and the maturityof integrated technology,flexible and wearable gas sensors play an increasingrole in gas analysis.This review highlights recent advances of smart gassensors in diverse applications.The structural components and fundamentalprinciples of electronic and optoelectronic gas sensors are described,andflexible and wearable gas sensor devices are highlighted.Moreover,sensorarray with artificial intelligence algorithms and smart gas sensors in“Internet of Things”paradigm are introduced.Finally,the challengesand perspectives of smart gas sensors are discussed regarding the future need of gas sensors for smart city and healthy living.展开更多
The complex wiring,bulky data collection devices,and difficulty in fast and on-site data interpretation significantly limit the practical application of flexible strain sensors as wearable devices.To tackle these chal...The complex wiring,bulky data collection devices,and difficulty in fast and on-site data interpretation significantly limit the practical application of flexible strain sensors as wearable devices.To tackle these challenges,this work develops an artificial intelligenceassisted,wireless,flexible,and wearable mechanoluminescent strain sensor system(AIFWMLS)by integration of deep learning neural network-based color data processing system(CDPS)with a sandwich-structured flexible mechanoluminescent sensor(SFLC)film.The SFLC film shows remarkable and robust mechanoluminescent performance with a simple structure for easy fabrication.The CDPS system can rapidly and accurately extract and interpret the color of the SFLC film to strain values with auto-correction of errors caused by the varying color temperature,which significantly improves the accuracy of the predicted strain.A smart glove mechanoluminescent sensor system demonstrates the great potential of the AIFWMLS system in human gesture recognition.Moreover,the versatile SFLC film can also serve as a encryption device.The integration of deep learning neural network-based artificial intelligence and SFLC film provides a promising strategy to break the“color to strain value”bottleneck that hinders the practical application of flexible colorimetric strain sensors,which could promote the development of wearable and flexible strain sensors from laboratory research to consumer markets.展开更多
Multimodal sensor fusion can make full use of the advantages of various sensors,make up for the shortcomings of a single sensor,achieve information verification or information security through information redundancy,a...Multimodal sensor fusion can make full use of the advantages of various sensors,make up for the shortcomings of a single sensor,achieve information verification or information security through information redundancy,and improve the reliability and safety of the system.Artificial intelligence(AI),referring to the simulation of human intelligence in machines that are programmed to think and learn like humans,represents a pivotal frontier in modern scientific research.With the continuous development and promotion of AI technology in Sensor 4.0 age,multimodal sensor fusion is becoming more and more intelligent and automated,and is expected to go further in the future.With this context,this review article takes a comprehensive look at the recent progress on AI-enhanced multimodal sensors and their integrated devices and systems.Based on the concept and principle of sensor technologies and AI algorithms,the theoretical underpinnings,technological breakthroughs,and pragmatic applications of AI-enhanced multimodal sensors in various fields such as robotics,healthcare,and environmental monitoring are highlighted.Through a comparative study of the dual/tri-modal sensors with and without using AI technologies(especially machine learning and deep learning),AI-enhanced multimodal sensors highlight the potential of AI to improve sensor performance,data processing,and decision-making capabilities.Furthermore,the review analyzes the challenges and opportunities afforded by AI-enhanced multimodal sensors,and offers a prospective outlook on the forthcoming advancements.展开更多
Ten physical and environmental variables collected from an on-the-go soil sensor at two field sites (MF3E and MF11S) in Mississippi, USA, were analyzed to assess soil variability and the interrelationships among the m...Ten physical and environmental variables collected from an on-the-go soil sensor at two field sites (MF3E and MF11S) in Mississippi, USA, were analyzed to assess soil variability and the interrelationships among the measurements. At MF3E, moderate variability was observed in apparent electrical conductivity shallow (ECas), slope, and ECa ratio measurements, with coefficients of variation ranging from 20% to 27%. In contrast, MF11S exhibited higher variability, particularly in ECas and ECad (deep) measurements, which exceeded 30% in their coefficient of variation values, indicating significant differences in soil composition and moisture content. Correlation analysis revealed strong positive relationships between the near-infrared-to-red ratio and red reflectance (r = 0.897***) soil values at MF3E. MF11S demonstrated a strong negative correlation between ECas and ECad readings with the x-coordinate (r ***). Scatter plots and fitted models illustrated the complexity of relationships, with many showing nonlinear trends. These findings emphasize the need for continuous monitoring and advanced modeling to understand the dynamic nature of soil properties and their implications for agricultural practices. Future research should explore the underlying mechanisms driving variability in the soil characteristics to enhance soil management strategies at the study sites.展开更多
NOx sensors, as a core component of diesel engine exhaust treatment system, play an important role in exhaust emission control, which can accurately and quickly detect the NOx and O2 concentration. It has become a nec...NOx sensors, as a core component of diesel engine exhaust treatment system, play an important role in exhaust emission control, which can accurately and quickly detect the NOx and O2 concentration. It has become a necessary option for the detection of existing exhaust emission standards. At present, there is limited and scattered information on knowledge and test methods of NOx sensors, the research of NOx sensors has become a challenging research topic at home and abroad. Based on these requirements, the article systematically integrates the knowledge of principle and testing methods. First of all, through introducing functional description of NOx sensors and the basic principle of NOx sensors, the relevant scholars can have an overall understanding of the product and master the operation mode of products. Secondly, the current status of performance test bench and methods of NOx sensors were described, which can contribute to having a clear understanding of the development process. After that, a new structure of NOx sensors test bench was purposed, which contains six major units including standard gas source, gas mixing unit, analyzer measurement unit, sensor measurement unit, data processing and display unit, exhaust gas treatment unit. And the test bench was validated. The experimental results show that the test bench has the advantages of high-repeatability, high reliability and low cost. And it can realize automatic detection of multiple target values, which is worthy further promotion. Thereby, the article can contribute to the development of its technology indirectly.展开更多
Nowadays,force sensors play an important role in industrial production,electronic information,medical health,and many other fields.Two-dimensional material-based filed effect transistor(2D-FET)sensors are competitive ...Nowadays,force sensors play an important role in industrial production,electronic information,medical health,and many other fields.Two-dimensional material-based filed effect transistor(2D-FET)sensors are competitive with nano-level size,lower power consumption,and accurate response.However,few of them has the capability of impulse detection which is a path function,expressing the cumulative effect of the force on the particle over a period of time.Herein we fabricated the flexible polymethyl methacrylate(PMMA)gate dielectric MoS_(2)-FET for force and impulse sensor application.We systematically investigated the responses of the sensor to constant force and varying forces,and achieved the conversion factors of the drain current signals(I_(ds))to the detected impulse(I).The applied force was detected and recorded by I_(ds)with a low power consumption of~30 nW.The sensitivity of the device can reach~8000%and the 4×1 sensor array is able to detect and locate the normal force applied on it.Moreover,there was almost no performance loss for the device as left in the air for two months.展开更多
Artificial sensory systems mimic the five human senses to facilitate data interaction between the real and virtual worlds.Accurate data analysis is crucial for converting external stimuli from each artificial sense in...Artificial sensory systems mimic the five human senses to facilitate data interaction between the real and virtual worlds.Accurate data analysis is crucial for converting external stimuli from each artificial sense into user-relevant information,yet conventional signal processing methods struggle with the massive scale,noise,and artificial sensory systems characteristics of data generated by artificial sensory devices.Integrating artificial intelligence(AI)is essential for addressing these challenges and enhancing the performance of artificial sensory systems,making it a rapidly growing area of research in recent years.However,no studies have systematically categorized the output functions of these systems or analyzed the associated AI algorithms and data processing methods.In this review,we present a systematic overview of the latest AI techniques aimed at enhancing the cognitive capabilities of artificial sensory systems replicating the five human senses:touch,taste,vision,smell,and hearing.We categorize the AI-enabled capabilities of artificial sensory systems into four key areas:cognitive simulation,perceptual enhancement,adaptive adjustment,and early warning.We introduce specialized AI algorithms and raw data processing methods for each function,designed to enhance and optimize sensing performance.Finally,we offer a perspective on the future of AI-integrated artificial sensory systems,highlighting technical challenges and potential real-world application scenarios for further innovation.Integration of AI with artificial sensory systems will enable advanced multimodal perception,real-time learning,and predictive capabilities.This will drive precise environmental adaptation and personalized feedback,ultimately positioning these systems as foundational technologies in smart healthcare,agriculture,and automation.展开更多
基金Supported by the Guangdong-Hong Kong-Macao Joint Laboratory on Micro-Nano Manufacturing Technology,China(No.2021LSYS004)Guangdong Provincial Key Laboratory of Sustainable Biomimetic Materials and Green Energy,China(No.2024B1212010003)。
文摘Monitoring biogenic amines,which are metabolic byproducts of shrimp spoilage,is crucial for assessing food quality.Currently,most detection methods for biogenic amines suffer from limitations such as time-consuming procedures,complex operations,and delayed results.Colorimetric analysis techniques have gained attention in recent years due to their advantages of short analysis time,simple operation,and suitability for on-site testing.This study successfully developed a series of colorimetric sensor platforms for biogenic amines by loading the natural active ingredient curcumin(CUR)and its derivative of Boron complex BFCUR onto filter paper and electrospun nanofibre films(ENFs),respectively.By analyzing the color response differences of these sensors upon contact with biogenic amines,the colorimetric sensors with superior detection performance were selected and further applied to the visual monitoring and indication of shrimp spoilage processes.
基金supported by the National Key Research and Development Program of China(2023YFB3809800)the National Natural Science Foundation of China(52172249,52525601)+2 种基金the Chinese Academy of Sciences Talents Program(E2290701)the Jiangsu Province Talents Program(JSSCRC2023545)the Special Fund Project of Carbon Peaking Carbon Neutrality Science and Technology Innovation of Jiangsu Province(BE2022011).
文摘Flexible fiber sensors,However,traditional methods face challenges in fabricating low-cost,large-scale fiber sensors.In recent years,the thermal drawing process has rapidly advanced,offering a novel approach to flexible fiber sensors.Through the preform-tofiber manufacturing technique,a variety of fiber sensors with complex functionalities spanning from the nanoscale to kilometer scale can be automated in a short time.Examples include temperature,acoustic,mechanical,chemical,biological,optoelectronic,and multifunctional sensors,which operate on diverse sensing principles such as resistance,capacitance,piezoelectricity,triboelectricity,photoelectricity,and thermoelectricity.This review outlines the principles of the thermal drawing process and provides a detailed overview of the latest advancements in various thermally drawn fiber sensors.Finally,the future developments of thermally drawn fiber sensors are discussed.
基金supported by the National Natural Science Foundation of China(General Program)under Grant 52571385National Key R&D Program of China(Grant No.2024YFC2815000 and No.2024YFB3816000)+12 种基金Open Fund of State Key Laboratory of Deep-sea Manned Vehicles(Grant No.2025SKLDMV07)Shenzhen Science and Technology Program(WDZC20231128114452001,JCYJ20240813112107010 and JCYJ20240813111910014)the Tsinghua SIGS Scientific Research Startup Fund(QD2022021C)the Dreams Foundation of Jianghuai Advance Technology Center(2023-ZM 01 Z006)the Ocean Decade International Cooperation Center(ODCC)(GHZZ3702840002024020000026)Shenzhen Key Laboratory of Advanced Technology for Marine Ecology(ZDSYS20230626091459009)Shenzhen Science and Technology Program(No.KJZD20240903100905008)the National Natural Science Foundation of China(No.22305141)Pearl River Talent Program(No.2023QN10C114)General Program of Guangdong Province(No.2025A1515011700)the Guangdong Innovative and Entrepreneurial Research Team Program(2023ZT10C040)Scientific Research Foundation from Shenzhen Finance Bureau(No.GJHZ20240218113600002)Tsinghua University(JC2023001).
文摘Developing effective,versatile,and high-precision sensing interfaces remains a crucial challenge in human-machine-environment interaction applications.Despite progress in interaction-oriented sensing skins,limitations remain in unit-level reconfiguration,multiaxial force and motion sensing,and robust operation across dynamically changing or irregular surfaces.Herein,we develop a reconfigurable omnidirectional triboelectric whisker sensor array(RO-TWSA)comprising multiple sensing units that integrate a triboelectric whisker structure(TWS)with an untethered hydro-sealing vacuum sucker(UHSVS),enabling reversibly portable deployment and omnidirectional perception across diverse surfaces.Using a simple dual-triangular electrode layout paired with MXene/silicone nanocomposite dielectric layer,the sensor unit achieves precise omnidirectional force and motion sensing with a detection threshold as low as 0.024 N and an angular resolution of 5°,while the UHSVS provides reliable and reversible multi-surface anchoring for the sensor units by involving a newly designed hydrogel combining high mechanical robustness and superior water absorption.Extensive experiments demonstrate the effectiveness of RO-TWSA across various interactive scenarios,including teleoperation,tactile diagnostics,and robotic autonomous exploration.Overall,RO-TWSA presents a versatile and high-resolution tactile interface,offering new avenues for intelligent perception and interaction in complex real-world environments.
基金supported by the Basic Science Research Program(2023R1A2C3004336,RS-202300243807)&Regional Leading Research Center(RS-202400405278)through the National Research Foundation of Korea(NRF)grant funded by the Korea Government(MSIT)。
文摘Wearable sensors integrated with deep learning techniques have the potential to revolutionize seamless human-machine interfaces for real-time health monitoring,clinical diagnosis,and robotic applications.Nevertheless,it remains a critical challenge to simultaneously achieve desirable mechanical and electrical performance along with biocompatibility,adhesion,self-healing,and environmental robustness with excellent sensing metrics.Herein,we report a multifunctional,anti-freezing,selfadhesive,and self-healable organogel pressure sensor composed of cobalt nanoparticle encapsulated nitrogen-doped carbon nanotubes(CoN CNT)embedded in a polyvinyl alcohol-gelatin(PVA/GLE)matrix.Fabricated using a binary solvent system of water and ethylene glycol(EG),the CoN CNT/PVA/GLE organogel exhibits excellent flexibility,biocompatibility,and temperature tolerance with remarkable environmental stability.Electrochemical impedance spectroscopy confirms near-stable performance across a broad humidity range(40%-95%RH).Freeze-tolerant conductivity under sub-zero conditions(-20℃)is attributed to the synergistic role of CoN CNT and EG,preserving mobility and network integrity.The Co N CNT/PVA/GLE organogel sensor exhibits high sensitivity of 5.75 k Pa^(-1)in the detection range from 0 to 20 k Pa,ideal for subtle biomechanical motion detection.A smart human-machine interface for English letter recognition using deep learning achieved 98%accuracy.The organogel sensor utility was extended to detect human gestures like finger bending,wrist motion,and throat vibration during speech.
基金supported by the NSFC(12474071)Natural Science Foundation of Shandong Province(ZR2024YQ051,ZR2025QB50)+6 种基金Guangdong Basic and Applied Basic Research Foundation(2025A1515011191)the Shanghai Sailing Program(23YF1402200,23YF1402400)funded by Basic Research Program of Jiangsu(BK20240424)Open Research Fund of State Key Laboratory of Crystal Materials(KF2406)Taishan Scholar Foundation of Shandong Province(tsqn202408006,tsqn202507058)Young Talent of Lifting engineering for Science and Technology in Shandong,China(SDAST2024QTB002)the Qilu Young Scholar Program of Shandong University。
文摘As emerging two-dimensional(2D)materials,carbides and nitrides(MXenes)could be solid solutions or organized structures made up of multi-atomic layers.With remarkable and adjustable electrical,optical,mechanical,and electrochemical characteristics,MXenes have shown great potential in brain-inspired neuromorphic computing electronics,including neuromorphic gas sensors,pressure sensors and photodetectors.This paper provides a forward-looking review of the research progress regarding MXenes in the neuromorphic sensing domain and discussed the critical challenges that need to be resolved.Key bottlenecks such as insufficient long-term stability under environmental exposure,high costs,scalability limitations in large-scale production,and mechanical mismatch in wearable integration hinder their practical deployment.Furthermore,unresolved issues like interfacial compatibility in heterostructures and energy inefficiency in neu-romorphic signal conversion demand urgent attention.The review offers insights into future research directions enhance the fundamental understanding of MXene properties and promote further integration into neuromorphic computing applications through the convergence with various emerging technologies.
基金partially supported by the National Natural Science Foundation of China(Nos.11804120,61827822,and 22275072)Guangdong Basic and Applied Basic Research Foundation(No.2023A1515030209)+1 种基金Research Projects from Guangzhou(Nos.2023A03J0018 and 2024A04J3712)Fundamental Research Funds for the Central Universities(No.21623412).
文摘Fiber-structured ion sensors have gained traction in health monitoring and medical diagnostics owing to their structural flexibility,enhanced sensitivity,and suitability for integration into wearable devices.This study employed a simple and efficient solutionbased process to fabricate nanofibers containing aggregation-induced emission(AIE)dyes.The resulting AIE nanofibers exhibited stable and intense fluorescence,nanosecond fluorescence lifetime,and low-loss light transport when functioning as active waveguides.Additionally,crossed nanofiber intersections exhibited diffraction-limited emission spots.The AIE nanofibers demonstrate efficient and ionspecific fluorescence quenching in response to Ag^(+).These results support the development of sensing units capable of operating in liquid environments or in direct contact with skin or tissues,facilitating real-time monitoring of ion concentrations for personalized healthcare management.
基金the financial support of this work by the National Natural Science Foundation of China(No.52373093)Excellent Youth Found of Natural Science Foundation of Henan Province(No.242300421062)+1 种基金Central Plains Youth Top notch Talent Program of Henan Provincethe 111 project(No.D18023).
文摘The advancement of wearable sensing technologies demands multifunctional materials that integrate high sensitivity,environmental resilience,and intelligent signal processing.In this work,a flexible hydrophobic conductive yarn(FCB@SY)featuring a controllable microcrack structure is developed via a synergistic approach combining ultrasonic swelling and non-solvent induced phase separation(NIPS).By embedding a robust conductive network and engineering microcrack morphology,the resulting sensor achieves an ultrahigh gauge factor(GF≈12,670),an ultrabroad working range(0%-547%),a low detection limit(0.5%),rapid response/recovery time(140 ms/140 ms),and outstanding durability over 10,000 cycles.Furthermore,the hydrophobic surface endowed by conductive coatings imparts exceptional chemical stability against acidic and alkaline environments,as well as reliable waterproof performance.This enables consistent functionality under harsh conditions,including underwater operation.Integrated with machine learning algorithms,the FCB@SY-based intelligent sensing system demonstrates dualmode capabilities in human motion tracking and gesture recognition,offering significant potential for applications in wearable electronics,human-machine interfaces,and soft robotics.
基金supported by the National Natural Science Foundation of China(No.52475580)the Special Foundation of the Taishan Scholar Project(No.tsqn202211077)+3 种基金the Shandong Provincial Natural Science Foundation(No.ZR2023ME118)the Open Project of State Key Laboratory of Chemical Safety(No.SKLCS-2024020)the Fundamental Research Funds for the Central Universities(No.24CX02014A)the Fund of State Key Laboratory of Deep Oil and Gas,China University of Petroleum(East China).
文摘In the context of the rapid development of artificial intelligence and robotics,their application scenarios are continuously expanding to a variety of complex environments,with increasing attention being paid to the use of flexible sensors in lowtemperature environments.In this study,an ionic hydrogel was synthesized using acrylamide(AM),hydroxyethyl cellulose(HEC),and lithium chloride(LiCl)as composites.This hydrogel exhibits high adhesion,excellent sensitivity(gauge factor(GF)=2.84),rapid response time(100 ms),exceptional stretch ability(>1776%),high toughness(2.5 MJ/m^(3)),and the ability to maintain detectability at low temperatures(-60℃).HEC imparts reliable mechanical properties to the sensor through hydrogen bonding interactions of its hydroxyl groups.LiCl ensures that the sensor has outstanding antifreezing properties,maintains good conductivity and mechanical performance.Used for robotic attitude detection,the sensor demonstrated accurate recognition of various joint movements at both 20 and -20℃.This technology was extended to industrial operations and maintenance,where a mechanical claw was used to grasp parts at both room temperature and low temperature.A convolutional neural network deep learning algorithm was employed to identify and classify eight types of parts,achieving an impressive recognition accuracy of 98.8%.The polyacrylamide(PAM)/HEC/LiCl hydrogel sensor demonstrates the capability for wide-temperature range detection in flexible robotics,holding significant potential for future applications in human-machine interaction,tactile perception,and related fields.
基金funded by the National Natural Science Foundation of China(Grant Nos.62322410,52272168,624B2135,61804047)the Fundamental Research Funds for the Central Universities(No.WK2030000103)。
文摘Human action recognition(HAR)is crucial for the development of efficient computer vision,where bioinspired neuromorphic perception visual systems have emerged as a vital solution to address transmission bottlenecks across sensor-processor interfaces.However,the absence of interactions among versatile biomimicking functionalities within a single device,which was developed for specific vision tasks,restricts the computational capacity,practicality,and scalability of in-sensor vision computing.Here,we propose a bioinspired vision sensor composed of a Ga N/Al N-based ultrathin quantum-disks-in-nanowires(QD-NWs)array to mimic not only Parvo cells for high-contrast vision and Magno cells for dynamic vision in the human retina but also the synergistic activity between the two cells for in-sensor vision computing.By simply tuning the applied bias voltage on each QD-NW-array-based pixel,we achieve two biosimilar photoresponse characteristics with slow and fast reactions to light stimuli that enhance the in-sensor image quality and HAR efficiency,respectively.Strikingly,the interplay and synergistic interaction of the two photoresponse modes within a single device markedly increased the HAR recognition accuracy from 51.4%to 81.4%owing to the integrated artificial vision system.The demonstration of an intelligent vision sensor offers a promising device platform for the development of highly efficient HAR systems and future smart optoelectronics.
文摘Diabetes mellitus represents a major global health issue,driving the need for noninvasive alternatives to traditional blood glucose monitoring methods.Recent advancements in wearable technology have introduced skin-interfaced biosensors capable of analyzing sweat and skin biomarkers,providing innovative solutions for diabetes diagnosis and monitoring.This review comprehensively discusses the current developments in noninvasive wearable biosensors,emphasizing simultaneous detection of biochemical biomarkers(such as glucose,cortisol,lactate,branched-chain amino acids,and cytokines)and physiological signals(including heart rate,blood pressure,and sweat rate)for accurate,personalized diabetes management.We explore innovations in multimodal sensor design,materials science,biorecognition elements,and integration techniques,highlighting the importance of advanced data analytics,artificial intelligence-driven predictive algorithms,and closed-loop therapeutic systems.Additionally,the review addresses ongoing challenges in biomarker validation,sensor stability,user compliance,data privacy,and regulatory considerations.A holistic,multimodal approach enabled by these next-generation wearable biosensors holds significant potential for improving patient outcomes and facilitating proactive healthcare interventions in diabetes management.
基金supported by the National Natural Science Foundation of China(NSFC 52175281,52475315)Youth Innovation Promotion Association of CAS(2021382)。
文摘The growing prevalence of exercise-induced tibial stress fractures demands wearable sensors capable of monitoring dynamic musculoskeletal loads with medical-grade precision.While flexible pressure-sensing insoles show clinical potential,their development has been hindered by the intrinsic trade-off between high sensitivity and full-range linearity(R^(2)>0.99 up to 1 MPa)in conventional designs.Inspired by the tactile sensing mechanism of human skin,where dermal stratification enables wide-range pressure adaptation and ion-channelregulated signaling maintains linear electrical responses,we developed a dual-mechanism flexible iontronic pressure sensor(FIPS).This innovative design synergistically combines two bioinspired components:interdigitated fabric microstructures enabling pressure-proportional contact area expansion(αP1/3)and iontronic film facilitating self-adaptive ion concentration modulation(αP^(2/3)),which together generate a linear capacitance-pressure response(CαP).The FIPS achieves breakthrough performance:242 kPa^(-1)sensitivity with 0.997linearity across 0-1 MPa,yielding a record linear sensing factor(LSF=242,000).The design is validated across various substrates and ionic materials,demonstrating its versatility.Finally,the FIPS-driven design enables a smart insole demonstrating 1.8%error in tibial load assessment during gait analysis,outperforming nonlinear counterparts(6.5%error)in early fracture-risk prediction.The biomimetic design framework establishes a universal approach for developing high-performance linear sensors,establishing generalized principles for medical-grade wearable devices.
文摘Aeromagnetic data for center-east Cameroon between the latitudes 3.5° to 4.5°N and longitudes 12° to 12.5°E are used to further study the subsurface area of this part of the geological Province of Central Africa and the Congo Craton. The GIS and GEOSOFT v6.5 softwares are used to treat the data. This analysis enabled us to explore our study area from surface right to the base. The Tilt Angle method is used to delineate geological structures and to estimate the depth. The Euler’s deconvolution method is used to estimate the specific depth of structural contacts. We estimate the northern boundary of the Congo Craton and southern boundary of the Pan-African starting from 3°7'N of West to 3°75'N of East. Its depth is estimated around 2.6 km for deep and 0.1 km for shallow while the direction is WSW-ENE and the NW slope varies from 30° to 60°. We obtain that main and minor lineaments exist throughout, from the surface to the base of the area with their principal direction being SW-NE. We also obtain the vertical gradient contact and the quasihorizontal contact. This is proof of the subduction of the Pan-African belt under the Congo Craton due to the intense collision which caused the rejuvenation of the crust. The main consequence of this collision is the formation of pudding and fold structures, beginning from the superficial part right to the base and which caused the intrusion of schistose, chlorite-schist, quartzite in the micaschist and the intrusions of gneiss and garnetiferous schist in the migmatite. In our study, we highlight the presence of 37 major and 523 minor lineaments that localize the circulation of minerals. The probable slope of the lineaments in the northern part of the region varies from 30° to 60° in a SE direction while in the southern part, and it varies from 30° to 60° in a NW direction.
基金supported by the National Natural Science Foundation of China(No.22376159)the Fundamental Research Funds for the Central Universities.
文摘Gas sensor is an indispensable part of modern society withwide applications in environmental monitoring,healthcare,food industry,public safety,etc.With the development of sensor technology,wireless communication,smart monitoring terminal,cloud storage/computing technology,and artificial intelligence,smart gas sensors represent the future of gassensing due to their merits of real-time multifunctional monitoring,earlywarning function,and intelligent and automated feature.Various electronicand optoelectronic gas sensors have been developed for high-performancesmart gas analysis.With the development of smart terminals and the maturityof integrated technology,flexible and wearable gas sensors play an increasingrole in gas analysis.This review highlights recent advances of smart gassensors in diverse applications.The structural components and fundamentalprinciples of electronic and optoelectronic gas sensors are described,andflexible and wearable gas sensor devices are highlighted.Moreover,sensorarray with artificial intelligence algorithms and smart gas sensors in“Internet of Things”paradigm are introduced.Finally,the challengesand perspectives of smart gas sensors are discussed regarding the future need of gas sensors for smart city and healthy living.
基金funded by the National Natural Science Foundation of China(52475580)the Special Foundation of the Taishan Scholar Project(tsqn202211077,tsqn202311077)+3 种基金Shandong Provincial Excellent Overseas Young Scholar Foundation(2023HWYQ-069)the Shandong Provincial Natural Science Foundation(ZR2023ME118,ZR2023QF080)the Natural Science Foundation of Qingdao City(23-2-1-219-zyyd-jch,23-2-1-111-zyyd-jch)the Fundamental Research Funds for the Central Universities(23CX06032A).
文摘The complex wiring,bulky data collection devices,and difficulty in fast and on-site data interpretation significantly limit the practical application of flexible strain sensors as wearable devices.To tackle these challenges,this work develops an artificial intelligenceassisted,wireless,flexible,and wearable mechanoluminescent strain sensor system(AIFWMLS)by integration of deep learning neural network-based color data processing system(CDPS)with a sandwich-structured flexible mechanoluminescent sensor(SFLC)film.The SFLC film shows remarkable and robust mechanoluminescent performance with a simple structure for easy fabrication.The CDPS system can rapidly and accurately extract and interpret the color of the SFLC film to strain values with auto-correction of errors caused by the varying color temperature,which significantly improves the accuracy of the predicted strain.A smart glove mechanoluminescent sensor system demonstrates the great potential of the AIFWMLS system in human gesture recognition.Moreover,the versatile SFLC film can also serve as a encryption device.The integration of deep learning neural network-based artificial intelligence and SFLC film provides a promising strategy to break the“color to strain value”bottleneck that hinders the practical application of flexible colorimetric strain sensors,which could promote the development of wearable and flexible strain sensors from laboratory research to consumer markets.
基金supported by the National Natural Science Foundation of China(No.62404111)Natural Science Foundation of Jiangsu Province(No.BK20240635)+2 种基金Natural Science Foundation of the Jiangsu Higher Education Institutions of China(No.24KJB510025)Natural Science Research Start-up Foundation of Recruiting Talents of Nanjing University of Posts and Telecommunications(No.NY223157 and NY223156)Opening Project of Advanced Inte-grated Circuit Package and Testing Research Center of Jiangsu Province(No.NTIKFJJ202303).
文摘Multimodal sensor fusion can make full use of the advantages of various sensors,make up for the shortcomings of a single sensor,achieve information verification or information security through information redundancy,and improve the reliability and safety of the system.Artificial intelligence(AI),referring to the simulation of human intelligence in machines that are programmed to think and learn like humans,represents a pivotal frontier in modern scientific research.With the continuous development and promotion of AI technology in Sensor 4.0 age,multimodal sensor fusion is becoming more and more intelligent and automated,and is expected to go further in the future.With this context,this review article takes a comprehensive look at the recent progress on AI-enhanced multimodal sensors and their integrated devices and systems.Based on the concept and principle of sensor technologies and AI algorithms,the theoretical underpinnings,technological breakthroughs,and pragmatic applications of AI-enhanced multimodal sensors in various fields such as robotics,healthcare,and environmental monitoring are highlighted.Through a comparative study of the dual/tri-modal sensors with and without using AI technologies(especially machine learning and deep learning),AI-enhanced multimodal sensors highlight the potential of AI to improve sensor performance,data processing,and decision-making capabilities.Furthermore,the review analyzes the challenges and opportunities afforded by AI-enhanced multimodal sensors,and offers a prospective outlook on the forthcoming advancements.
文摘Ten physical and environmental variables collected from an on-the-go soil sensor at two field sites (MF3E and MF11S) in Mississippi, USA, were analyzed to assess soil variability and the interrelationships among the measurements. At MF3E, moderate variability was observed in apparent electrical conductivity shallow (ECas), slope, and ECa ratio measurements, with coefficients of variation ranging from 20% to 27%. In contrast, MF11S exhibited higher variability, particularly in ECas and ECad (deep) measurements, which exceeded 30% in their coefficient of variation values, indicating significant differences in soil composition and moisture content. Correlation analysis revealed strong positive relationships between the near-infrared-to-red ratio and red reflectance (r = 0.897***) soil values at MF3E. MF11S demonstrated a strong negative correlation between ECas and ECad readings with the x-coordinate (r ***). Scatter plots and fitted models illustrated the complexity of relationships, with many showing nonlinear trends. These findings emphasize the need for continuous monitoring and advanced modeling to understand the dynamic nature of soil properties and their implications for agricultural practices. Future research should explore the underlying mechanisms driving variability in the soil characteristics to enhance soil management strategies at the study sites.
文摘NOx sensors, as a core component of diesel engine exhaust treatment system, play an important role in exhaust emission control, which can accurately and quickly detect the NOx and O2 concentration. It has become a necessary option for the detection of existing exhaust emission standards. At present, there is limited and scattered information on knowledge and test methods of NOx sensors, the research of NOx sensors has become a challenging research topic at home and abroad. Based on these requirements, the article systematically integrates the knowledge of principle and testing methods. First of all, through introducing functional description of NOx sensors and the basic principle of NOx sensors, the relevant scholars can have an overall understanding of the product and master the operation mode of products. Secondly, the current status of performance test bench and methods of NOx sensors were described, which can contribute to having a clear understanding of the development process. After that, a new structure of NOx sensors test bench was purposed, which contains six major units including standard gas source, gas mixing unit, analyzer measurement unit, sensor measurement unit, data processing and display unit, exhaust gas treatment unit. And the test bench was validated. The experimental results show that the test bench has the advantages of high-repeatability, high reliability and low cost. And it can realize automatic detection of multiple target values, which is worthy further promotion. Thereby, the article can contribute to the development of its technology indirectly.
基金financially supported by the National Natural Science Foundation of China(Nos.52272160,U2330112,and 52002254)Sichuan Science and Technology Foundation(Nos.2020YJ0262,2021YFH0127,2022YFH0083,2022YFSY0045,and 2023YFSY0002)+1 种基金the Chunhui Plan of Ministry of Education,Fundamental Research Funds for the Central Universities,China(No.YJ201893)the Foundation of Key Laboratory of Lidar and Device,Sichuan Province,China(No.LLD2023-006)。
文摘Nowadays,force sensors play an important role in industrial production,electronic information,medical health,and many other fields.Two-dimensional material-based filed effect transistor(2D-FET)sensors are competitive with nano-level size,lower power consumption,and accurate response.However,few of them has the capability of impulse detection which is a path function,expressing the cumulative effect of the force on the particle over a period of time.Herein we fabricated the flexible polymethyl methacrylate(PMMA)gate dielectric MoS_(2)-FET for force and impulse sensor application.We systematically investigated the responses of the sensor to constant force and varying forces,and achieved the conversion factors of the drain current signals(I_(ds))to the detected impulse(I).The applied force was detected and recorded by I_(ds)with a low power consumption of~30 nW.The sensitivity of the device can reach~8000%and the 4×1 sensor array is able to detect and locate the normal force applied on it.Moreover,there was almost no performance loss for the device as left in the air for two months.
基金supported by the National Research Foundation(NRF)grant funded by the Korean government(MSIT)(RS-2023-00211580,RS-2023-00237308).
文摘Artificial sensory systems mimic the five human senses to facilitate data interaction between the real and virtual worlds.Accurate data analysis is crucial for converting external stimuli from each artificial sense into user-relevant information,yet conventional signal processing methods struggle with the massive scale,noise,and artificial sensory systems characteristics of data generated by artificial sensory devices.Integrating artificial intelligence(AI)is essential for addressing these challenges and enhancing the performance of artificial sensory systems,making it a rapidly growing area of research in recent years.However,no studies have systematically categorized the output functions of these systems or analyzed the associated AI algorithms and data processing methods.In this review,we present a systematic overview of the latest AI techniques aimed at enhancing the cognitive capabilities of artificial sensory systems replicating the five human senses:touch,taste,vision,smell,and hearing.We categorize the AI-enabled capabilities of artificial sensory systems into four key areas:cognitive simulation,perceptual enhancement,adaptive adjustment,and early warning.We introduce specialized AI algorithms and raw data processing methods for each function,designed to enhance and optimize sensing performance.Finally,we offer a perspective on the future of AI-integrated artificial sensory systems,highlighting technical challenges and potential real-world application scenarios for further innovation.Integration of AI with artificial sensory systems will enable advanced multimodal perception,real-time learning,and predictive capabilities.This will drive precise environmental adaptation and personalized feedback,ultimately positioning these systems as foundational technologies in smart healthcare,agriculture,and automation.
